With the swift emergence of electronic medical information, the global popularity of mobile health (mHealth) services continues to increase steadily. This study aims to investigate the efficacy factors that directly or indirectly influence individuals’ acceptance of mHealth services. Based on the technology acceptance model, this research incorporates efficacy factors into the acceptance decision process. A research model was proposed involving the direct and indirect effects of self-efficacy and response-efficacy on acceptance intention, along with their moderating effects. The model and hypotheses were validated using data collected from a field survey of 650 potential service users. The results reveal that: (1) self-efficacy and response-efficacy are both positively associated with perceived ease of use; and (2) self-efficacy and response-efficacy moderate the impact of perceived usefulness toward adoption intention. Self-efficacy and response-efficacy both play an important role in individuals’ acceptance of mHealth services, which not only affect their perceived ease of use of mHealth services, but also positively moderate the effects of perceived usefulness on adoption intention. Our findings serve to provide recommendations that are specifically customized for mHealth service providers and their marketers.

Background: Mobile health (m-health) services are becoming increasingly popular in healthcare, but research on m-health adoption is rare. This study was designed to obtain a better understanding of m-health adoption intention. Materials and Methods: We conducted an empirical research of a 481-respondent sample consisting of 44.7% women and 55.3% men and developed a modified theory of reasoned action (TRA) model by incorporating the nonlinearities between attitude and subjective norms and the moderating effect of gender. Results: The results indicate that, based on the study population in China: (1) facilitating conditions, attitude, and subjective norms are significant predictors of m-health adoption intention; (2) the model including the nonlinearities enhances its explanatory ability; (3) males enjoy a higher level of m-health adoption intention compared with females; (4) the modified TRA model can predict men's behavior intention better than that of women; and (5) males have an Edgeworth–Pareto substitutability between attitude and subjective norms in predicting m-health adoption intention. Conclusions: Thus, we found gender differences in m-health adoption from the perspective of social psychology.

Background: Mobile health (m-health) services are becoming increasingly important and widely accepted. However, empirical studies on potential users' m-health acceptance behavior remain underexplored. Indeed, m-health adoption is not only a technology acceptance behavior, but also a health-related behavior. Materials and Methods: Based on the Protection Motivation Theory, this article explores users' m-health adoption behavior from the perspectives of threat appraisal and coping appraisal, and also examines the moderating role of gender and age through a survey of potential users. The survey was conducted among 500 potential m-health service participants. Results: Our results show that threat appraisal and coping appraisal factors influence adoption intention through attitude. It is also found that gender and age play different moderating roles with threat appraisal and coping appraisal factors. Conclusions: Gender and age play different roles between threat appraisal and coping appraisal factors in the acceptance of m-health. Implications for research and practice are discussed.

In recent years, the development of online health-consultation platforms has drawn significant research attention to online patient–doctor relationship development, particularly in developing countries, where there are limited health care resources for each patient. However, online interactional unfairness in patient–doctor relationship development has been largely overlooked in the context of information and communication technology (ICT). This study proposes and tests a model that examines how online interactional unfairness (ie, interpersonal unfairness and informational unfairness) influences online patient–doctor relationship quality and the contingent roles of a doctor’s professional seniority and a patient’s disease severity. Using archival data with 83,553 observations from a leading online health-consultation platform in China, this study employed rare-event logistic regression to test the model. The results show that online interpersonal unfairness and online informational unfairness have negative and positive effects on relationship-quality incentive, respectively, in the Chinese health care context and that a doctor’s professional seniority and a patient’s disease severity strengthen the link between unfairness perceptions and relationship-quality incentive. This study advances the knowledge of online patient–doctor relationship development in ICT-based health care in China and provides practical insights for online health care stakeholders for managing unfairness in the health care context.